*4.1.6 Impulse response function (IRF)*

The IRF analysis explains the effects of shocks (shock) on one variable from the other variables, both in the short term and in the long term. The IRF also analyzes on how long the shocks take place. The horizontal axis shows the period of the year, while the vertical axis shows the response value in percentage, as the following details:

#### *4.1.6.1 Impulse response FDR to NPF*

The first IRF analysis will explain the response received by the FDR to the *shock* of NPF. According to **Figure 3**, the response of the FDR if there was a shock from NPF is positive (+), where it shows an increase trend from periods 1 to 3. But, then in the 3rd to 10th period, the response of the FDR variable to NPF shock decreased. These results are consistent with findings from VECM estimation either in the short or long run where FDR will be fluctuating in short period and tends to be less volatile in the long run due to shocks from NPF. This condition indicates that liquidity risk in Islamic banks is only influenced by financing risk in the short run and decreases toward equilibrium in the long run.

#### *4.1.6.2 Impulse response FDR to BOPO*

**Figure 4** shows the response of FDR due to shocks coming from BOPO. Its responses are negative in the first three periods but tend to positive afterward. These conditions are consistent with VECM estimation where in the short run its relationship is negative, but positive in the long run. It indicates that liquidity risk is sensitive in both short and long runs due to shocks originated from operational risk.

influenced by the FDR variable which has a positive effect of 0.01%. Then, in the first lag, the BOPO variable is influenced by the NPF variable, which has a negative effect of 8.03%. Therefore, in the long run, only operational risk—proxied by

**Variable Coefficient t-Statistic partial**

D(FDR(1)) 0.255421 [2.50543] D(FDR(2)) 0.038103 [0.37947] D(FDR(3)) 0.271292 [2.86236] D(NPF(1)) 1.360963 [2.11235] D(NPF(2)) 0.37662 [0.59751] D(NPF(3)) 0.344605 [0.55659] D(BOPO(1)) 0.207859 [2.93623] D(BOPO(2)) 0.223429 [3.27360] D(BOPO(3)) 0.01964 [0.28727] C 0.112072 [0.60029]

D(NPF(1)) 0.081274 [0.77003] D(NPF(2)) 0.015491 [0.15002] D(NPF(3)) 0.404753 [3.99059] D(BOPO(1)) 0.015403 [1.32823] D(BOPO(2)) 0.023770 [2.12593] D(BOPO(3)) 0.005957 [0.53189] D(FDR(1)) 0.010509 [0.62922] D(FDR(2)) 0.015999 [0.97261] D(FDR(3)) 0.005072 [0.32666] C 0.008109 [0.26512]

D(BOPO(1)) 0.042771 [0.38050] D(BOPO(2)) 0.034201 [0.31558] D(BOPO(3)) 0.052325 [0.48200] D(FDR(1)) 0.122321 [0.75564] D(FDR(2)) 0.119351 [0.74857] D(FDR(3)) 0.224285 [1.49029] D(NPF(1)) 0.953621 [0.93213] D(NPF(2)) 0.600455 [0.59994] D(NPF(3)) 1.006292 [1.02358] C 0.101554 [0.34256]

FDR CointEq1 0.001081 [0.17523]

NPF CointEq1 0.197484 [2.69286]

BOPO CointEq1 0.282793 [3.19815]

BOPO—affects positively the liquidity risk, proxied by FDR.

*Sources: Author's calculation.*

*Banking and Finance*

*VECM in short term.*

**Table 6.**

**62**

**Figure 3.** *Impulse response FDR to NPF. Source: Author's calculation.*

*4.1.6.5 Impulse response variable BOPO to variable FDR*

*Impulse response NPF to BOPO. Source: Author's calculation.*

*Impulse response NPF to FDR. Source: Author's calculation.*

*Risk Analyses on Islamic Banks in Indonesia DOI: http://dx.doi.org/10.5772/intechopen.92245*

*4.1.6.6 Impulse response variable BOPO to variable NPF*

the short run, not in the long run.

Islamic bank.

**65**

**Figure 5.**

**Figure 6.**

**Figure 7** shows the response of BOPO due to shocks from FDR. The findings suggest initially it responds positively until the first three periods. However, the trend is negative in the long run. These conditions are consistent with VECM estimation where both variables have a negative relationship in the short run, but no relationship in the long run. It indicates that operational risk is only affected in

**Figure 8** shows the response of BOPO due to shocks from NPF. The findings suggest that BOPO responds positively in the first four periods due to shocks from NPF, but tend to decline in the long run. In this regard, these findings are consistent with VECM estimation where BOPO is sensitive due to the change of NPF. These conditions also indicate that operational risk is sensitive toward financing risk in

**Table 9** shows the summary of risk sensitivity based on originated shocks into Islamic banks. The findings suggest that the risks in Islamic banks are interrelated to each other, in either the short or long run. Specifically, **Table 9** suggests as follows:

**Figure 4.** *Impulse response FDR to BOPO. Source: Author's calculation.*

#### *4.1.6.3 Impulse response variable NPF to variable FDR*

**Figure 5** shows the response of NPF due to shocks from FDR. Results indicate that NPF responds negatively but only for less than two periods, and then it is stable toward its long-term movements. These findings are in line with VECM estimation where NPF is significantly affected by FDR in the short run, but not significant in the long run. It implies that financing risk exists and sensitive only in the short run due to liquidity risk, but not in the long run.

#### *4.1.6.4 Impulse response variable NPF to variable BOPO*

**Figure 6** shows the response of NPF due to shock from BOPO. Results suggest that in the first three periods, NPF responds positively and continues to increase in the long run. These findings are not linear with VECM estimation where NPF is suggested to be negatively influenced by BOPO, either short or long run. Furthermore, the findings suggest that financing risk is quite sensitive toward operational risk.

*Risk Analyses on Islamic Banks in Indonesia DOI: http://dx.doi.org/10.5772/intechopen.92245*

**Figure 5.** *Impulse response NPF to FDR. Source: Author's calculation.*

**Figure 6.** *Impulse response NPF to BOPO. Source: Author's calculation.*
